Our first experiment is taken from [1]}, the
task is to train a Riemannian flow generating a 4-modal distribution
defined on the \({\mathcal {S}}^2\)  sphere via a reverse-mode KL minimization. This
experiment allows quantitative comparison of the different models'
theoretical and practical expressiveness. We report results obtained
with their best performing models: a Möbius-spline flow and a
radial flow. The latter is an exponential-map flow with radial layers
(24 block of 1 component). We train a 5-block RCPM.
The exponential map and the intrinsic distance required for RCPMs are
closed-form for the sphere.
More implementation details are provided
in sec:additional-exps.
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